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Why going against the tide cannot bring you anything good!

Why going against the tide cannot bring you anything good!

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#noestimates Presentation Transcript

  • 1. #noestimates why going against the tide cannot bring you anything good! info@massimoiacolare.it @iacoware Massimo Iacolare linkedin
  • 2. Estimating sucks!
  • 3. Estimating sucks! End of story
  • 4. Estimating sucks! End of story Questions?
  • 5. #noestimates ‣nothing new, just a new (bigger) wave ‣lot of buzz, lately ‣Woody Zuill started the hashtag on twitter If you found estimates bring no value what would you do?
  • 6. Why so interested?
  • 7. Why so interested? I struggled against them for a long time
  • 8. Why so interested? I struggled against them for a long time I still see a lot of energy & morale wasted
  • 9. Software development …and why estimating (really) sucks! Part 1
  • 10. Software development is… …a complex beast!
  • 11. no best practices social interactions learning activity integration external factors
  • 12. non deterministic no best practices social interactions learning activity integration external factors
  • 13. Cynefin framework
  • 14. Cynefin framework Emergent vs Predictable
  • 15. ok, understood! lets get back to estimates
  • 16. Unreliable: adj not able to be relied upon, untrustwhorty
  • 17. How useful is a metric with 400% variance?
  • 18. Let’s see what makes estimates unreliable…
  • 19. Let’s see what makes estimates unreliable… as if being in a complex domain wasn’t enough…
  • 20. Asked at the beginning of a project
  • 21. Asked at the beginning of a project Someone said cone of uncertainty?
  • 22. Asked at the beginning of a project Someone said cone of uncertainty? projectknowledge time cone of uncertainty
  • 23. Cost of a feature =
  • 24. Cost of a feature = Essential complexity +
  • 25. Cost of a feature = Essential complexity Accidental complexity+ from “No silver bullet” Fred Brooks, 1995
  • 26. Cognitive biases
  • 27. Cognitive biases Optimism bias
  • 28. Cognitive biases Optimism bias Anchoring bias
  • 29. Cognitive biases Optimism bias Anchoring bias Availability bias
  • 30. Cognitive biases Optimism bias Anchoring bias Availability bias Selective perception
  • 31. Cognitive biases Optimism bias Anchoring bias Availability bias Selective perception Loss aversion List of cognitive biases
  • 32. oh wait, we have a cure…
  • 33. oh wait, we have a cure… estimate effort not duration!
  • 34. oh wait, we have a cure… estimate effort not duration! sorry dude, estimates are incurable… all issues are still valid, plus we lost the only metric business care about… duration
  • 35. oh wait, we have a cure… estimate effort not duration! sorry dude, estimates are incurable… all issues are still valid, plus we lost the only metric business care about… duration
  • 36. My point is… if you’re rigorous and determined you can make them work (someway, somewhere), but…
  • 37. My point is… if you’re rigorous and determined you can make them work (someway, somewhere), but… very easy to get derailed
  • 38. My point is… if you’re rigorous and determined you can make them work (someway, somewhere), but… very easy to get derailed insist on a wrong mindset
  • 39. Ask yourself…
  • 40. Ask yourself… Worth the effort?
  • 41. Ask yourself… Worth the effort? Are they a a mean or a goal?
  • 42. Why? Part 2
  • 43. Historical reasons
  • 44. Historical reasons management techniques derived from traditional businesses
  • 45. The impossible quest for predictability Management science’s impossible quest: in search of predictability
  • 46. Prioritization
  • 47. Prioritization estimates == prioritise on costs
  • 48. Prioritization estimates == prioritise on costs learning should be your first priority Introducing deliberate discovery
  • 49. Delivery date
  • 50. Delivery date order-of-magnitude estimates are enough
  • 51. Delivery date order-of-magnitude estimates are enough fixed-time fixed-budget more common and useful
  • 52. Ship steering
  • 53. Ship steering How far are we from the target?
  • 54. Ship steering How far are we from the target? You’re asking the wrong question…
  • 55. Part 3 the way out
  • 56. Few assumptions
  • 57. Few assumptions ‣ Relevant parts sits in the Complex Domain ‣ Unpredictable business ‣ Detailed planning won’t save us
  • 58. Few assumptions ‣ Relevant parts sits in the Complex Domain ‣ Unpredictable business ‣ Detailed planning won’t save us Few ideas…
  • 59. Establish a tight feedback loop at all levels: tdd, continuous delivery, customer
  • 60. Establish a tight feedback loop at all levels: tdd, continuous delivery, customer only thing that works in emergent domains
  • 61. Plan based on value
  • 62. Plan based on value Hint: there’s no value in sticking to the plan
  • 63. Just enough planning
  • 64. Just enough planning Just-in-time planning
  • 65. Just enough planning Just-in-time planning context changed assumptions debunked more knowledge
  • 66. Just enough planning Just-in-time planning context changed assumptions debunked more knowledge explore new options
  • 67. Iterate like there is no tomorrow
  • 68. Iterate like there is no tomorrow working in iterations doesn’t mean iterating Embrace uncertainty
  • 69. Become a master in slicing scope
  • 70. Become a master in slicing scope Login Catalog Add to cart Checkout
  • 71. Become a master in slicing scope Login Catalog Add to cart Checkout
  • 72. Become a master in slicing scope you’ll meet deadlines too! Login Catalog Add to cart Checkout
  • 73. estimate less code more
  • 74. Thanks! Questions? info@massimoiacolare.it @iacoware Massimo Iacolare linkedin
  • 75. I stand on the shoulders of giants Woody Zuill blog Vasco Duarte blog Neil Killick blog AgileCamp perfect flow - Gabriele Lana part1 - ITA AgileCamp perfect flow - Gabriele Lana part2 - ITA Estimation is the root of most software project failures Stop using story points The perils of estimation …and many, many more. Thank you all!